Enterprise AI Platform Engineer
AI summary of the role
This role bridges the AI Innovation Lab and production engineering at DISCO, transforming citizen-developed AI prototypes (Python, Workato, Claude Code) into secure, scalable enterprise systems.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Re-architect AI prototypes (Python, Workato, Claude Code) for secure, scalable enterprise deployment
- Design cloud infrastructure (AWS/Azure), implement CI/CD pipelines, and containerize applications (Docker/Kubernetes)
- Implement security measures: secrets management, encryption, audit logging, and compliance validation
- Design production-ready architectures for 1,000+ users and establish engineering standards
What you’ll bring
- 5-8 years of software engineering experience with production systems and full-stack development (Python/TypeScript)
- Deep expertise in cloud infrastructure (AWS/Azure), containerization (Docker/Kubernetes), and CI/CD pipelines
- Proven track record of transitioning MVPs to production or platform engineering experience
- Proficiency in Python, JavaScript/TypeScript, and modern frameworks
Technologies
Python · TypeScript · AWS · Azure · Docker · Kubernetes · Terraform · CloudFormation · GitHub Actions · Jenkins · PostgreSQL · Redis
About DISCO
Cloud-native litigation platform for law firms, corporate legal teams, and service providers spanning ediscovery, review, legal holds, requests, and AI-assisted fact investigation.
Public · 500–1000 people
Source and classification
Internal deployment & tooling · Evidence for this classification:
Your Impact The Enterprise AI Platform Engineer transforms citizen-developed AI prototypes (using Python, Workato, and Claude Code) into secure, scalable, production-grade enterprise systems. This role is a vital link between the AI Innovation Lab and production engineering, evolving experimental Minimum Viable Products (MVPs) into long-term corporate capabilities. What You'll Do Production Engineering and Deployment: Re-architect initial AI prototypes (Python, Workato, Claude Code) for secure, scalable enterprise deployment. This includes designing cloud infrastructure (AWS/Azure), implementing CI/CD pipelines, containerizing applications (Docker/Kubernetes), developing integration APIs, and setting up comprehensive monitoring and observability for all production AI systems. Security and Compliance: Ensure secure deployment by design, implementing robust secrets management and
More from the job description
Your Impact The Enterprise AI Platform Engineer transforms citizen-developed AI prototypes (using Python, Workato, and Claude Code) into secure, scalable, production-grade enterprise systems. This role is a vital link between the AI Innovation Lab and production engineering, evolving experimental Minimum Viable Products (MVPs) into long-term corporate capabilities. What You'll Do Production Engineering and Deployment: Re-architect initial AI prototypes (Python, Workato, Claude Code) for secure, scalable enterprise deployment. This includes designing cloud infrastructure (AWS/Azure), implementing CI/CD pipelines, containerizing applications (Docker/Kubernetes), developing integration APIs, and setting up comprehensive monitoring and observability for all production AI systems. Security and Compliance: Ensure secure deployment by design, implementing robust secrets management and protecting data through encryption at rest and in transit. This role also establishes comprehensive audit logging, partners on critical security reviews, and validates ongoing compliance with enterprise policies and regulatory standards. Solution Architecture and Design: The role involves reviewing prototypes to design production-ready and scalable architectures for 1,000+ users, while collaborating on technology selection and integration patterns. Additionally, the engineer establishes engineering [... source excerpt omitted ...] w and troubleshooting for prototype solutions, alongside building internal developer platforms and reusable infrastructure-as-code templates to accelerate development. A final key responsibility is training the team on DevOps practices and creating clear technical documentation for all stakeholders. Who You Are 5-8 years of software engineering experience focusing on production systems, full-stack development (Python/TypeScript), and RESTful API design. Deep expertise in cloud infrastructure (AWS/Azure), containerization (Docker/Kubernetes) and building robust DevOps CI/CD pipelines. Proven track record of transitioning MVPs to production environments or contributing to platform e
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